Lung disease is mainly characterized by the variations that occur in breathing sound of human being. The variations are characterized as wheezes, crackles, etc. Wheezes are one of the most important adventitious sounds in pulmonary system. They are observed in asthma, chronic obstructive pulmonary disease (COPD) and bronchitis. The current method of detecting a lung disease for example asthma involves usage of spirometers and stethoscope. The results with these techniques are not efficient. A wheezing detection system may help physicians to monitor patients over the long-term. This technique involves on board capture and processing methodology. This paper involves the system for breath sound acquisition and real time pre-processing and detection of abnormality in lung sounds using DSP processor. The aim of the system is to design and develop portable device for acquisition and detection of abnormality in lung sounds.

Lung Diseases, Stethoscope, DSP Processor, FFT, Wheeze, Android application

[1] Acharya, Jyotibdha Basu, Arindam Ser, Wee, “Feature Extraction Techniques for Low-Power Ambulatory Wheeze Detection Wearables”, 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2017) pp. 4574-4577.
[2] D. Chamberlain, J. Mofor, R. Fletcher, R. Kodgule, “Mobile Stethoscope and Signal Processing Algorithms for Pulmonary Screening and Diagnostics”, IEEE 2015 Global Humanitarian Technology Conference pp. 3074-3080
[3] Jianmin Zhang,Wee Ser,Jufeng Yu, T.T.Zhang., “A Novel Wheeze Detection Method For Wearable Monitoring System”, IEEE Computer Society., 2009.pp 331-334
[4] Bor-Shing Lin,Tian-Shiue Yen, “An FPGA based Rapid Wheezing detection System”, Int. J. Environ. Res Pubic Health, pp. 1573-1593, 2014.
[5] Dinko Oletic, Bruno Arsenali and Vedran Bilas, “Low-Power Wearable Respiratory Sound Sensing”, Sensors 2014 ISSN 1424-8220
[6] R.J.Riella, P.Nohama and J.M.Maia, “Method for automatic detection of wheezing in lung sounds”, Brazilian Journal of Medical and Biological Research., pp. 674-684, 2009.
[7] Sandra Reichert, “Analysis of Respiratory Sounds: State of the Art”, Clinical Medicine: Circulatory, Respiratory and Pulmonary Medicine 2008:2 45–58
[8] Styliani A. Taplidou, Leontios J. Hadjileontiadis, “Wheeze detection based on time-frequency analysis of breath sounds”, Computers in Biology and Medicine 37 (2007) 1073 – 1083
[9] Marcin Wiśniewski, Tomasz Zieliński, “Digital Analysis Methods of Wheezes in Asthma”, The International Conference on Signals and Electronic Systems, Gliwice, Poland, September 7-10, 2010.
[10] Sameer Alsmadia,Yasemin P. Kahyab, “Design of a DSP-based instrument for real-time classification of pulmonary sounds”, Computers in Biology and Medicine 38 (2008) 53 – 61
[11] Jayant V. Mankar, Prof. Sunil Kureel, “Analysis of Lung Diseases and Detecting Deformities in Human Lung by Classifying Lung Sounds”, International Journal of Research in Advent Technology, Vol.2, No.10, October 2014 E-ISSN: 2321-9637
[12] A.P. Mohod, A. Pankar, A Mohite, A. Dondalkar, A. Kadhe, Manish Naik, “Digital Health Record and Prescription”,International Journal of Scientific Research in Computer Sciences and Engineering, Vol.6 , Issue.1 , pp.60-62, Feb-2018
[13] J. Joseph, S. Devane, “Low Profile Microwave Band Pass Filter”, International Journal of Scientific Research in Network Security and Communication, Vol.5 , Issue.2 , pp.1-6, May-2017
[14] Shih-Hong Li,Bor-Shing Lin,Chen-Han Tsai,Cheng-Ta Yang and Bor-Shyh Lin,”Design of Wearable Breathing Sound Monitoring
System for Real-Time Wheeze Detection”, Sensors 2017, 17, 171; doi: 10.3390/s17010171